US11083392B2 - Bio-processor, bio-signal detecting system, and operation method of bio-processor - Google Patents

Abstract

A bio-processor includes a bioelectrical impedance sensor and a digital signal processor. The bioelectrical impedance sensor measures bioelectrical impedance during a sensing time including a portion of a settling time. The digital signal processor estimates a settled bioelectrical impedance value based on changes in the measured bioelectrical impedance. The digital signal processor generates bio-data based on the settled bioelectrical impedance value.

Description

CROSS-REFERENCE TO RELATED APPLICATIONS

This application claims priority under 35 U.S.C. § 119 to Korean Patent Provisional Application No. 10-2017-0089143 filed Jul. 13, 2017, in the Korean Intellectual Property Office, and Korean Patent Application No. 10-2017-0150733 filed Nov. 13, 2017, in the Korean Intellectual Property Office, the entire contents of each of which are hereby incorporated by reference.

BACKGROUND

Example embodiments of the inventive concepts described herein relate to processing bio-signals. For example, at least some example embodiments relate to, a bio-processor, a bio-signal detecting system, and/or an operation method of the bio-processor.

With the development of medical technologies, human life has been increased. As food information, medical information, health care information, and the like for leading healthy lives have been provided in various manners, there has been a growing interest in physical examination such as examination of body fat. For this purpose, a variety of electronic devices for simplifying detection of bio-signals and analysis of body composition based on the detected bio-signals have been developed.

Recently, a method for measuring and processing bio-signals using a wearable device may be utilized to check healthy states of human bodies such as body fat. The wearable device is worn on a user anytime and anywhere and may detect bio-signals and may process the bio-signals. Further, since a bio-processor included in the wearable device is an element that performs analysis of the bio-signals, a speed and accuracy associated with the bio-processor processing the bio-signal may increase in importance.

A conventional bio-processor may wait until a bio-signal provided from a user is settled and may analyze body composition based on the settled bio-signal. Until a bio-signal is settled, the user may be forced to maintain a contact state with an electronic device and also minimize motion. If a time until the bio-signal settles is long, the user may need to limit motion for a relatively long period of time and accuracy of the bio-signal may be reduced due to, for example, the user sweating during this relatively long period of time.

SUMMARY

Example embodiments of the inventive concepts provide a bio-processor for reducing a time when a bio-signal is measured and increasing accuracy of analyzed bio-data, a bio-signal detecting system, and/or an operation method of the bio-processor.

According to an example embodiment, a bio-processor may include a bioelectrical impedance sensor configured to measure a measured bioelectrical impedance during a sensing time such that the sensing time includes a portion of a settling time, the settling time being prior to the measured bioelectrical impedance reaching a settled bioelectrical impedance value; and a digital signal processor configured to, estimate the settled bioelectrical impedance value based on changes in the measured bioelectrical impedance, and generate bio-data based on the settled bioelectrical impedance value.

According to another example embodiment, a bio-signal detecting system may include an electrode device configured to supply an output current to outside the bio-signal detecting system, and to receive a sensing voltage based on the output current; a bioelectrical impedance sensor configured to sense the sensing voltage during a sensing time, and to measure changes in bioelectrical impedance corresponding to the sensing voltage, the sensing time including a portion of a settling time, the settling time being prior to the bioelectrical impedance reaching a settled bioelectrical impedance value; and a processor configured to estimate the settled bioelectrical impedance value based on the measured changes in the bioelectrical impedance.

According to another example embodiment, an operation method of a bio-processor may include measuring a sensing voltage during a portion of a settling time, the settling time being prior to a value of a bioelectrical impedance reaching a settled bioelectrical impedance value; modeling the value of the bioelectrical impedance for the settling time in a fitting function based on changes in the sensing voltage to generate a modeled fitting function; estimating the settled bioelectrical impedance value at a settled time based on the modeled fitting function, the settled time being after expiration of the settling time; and generating bio-data based on the estimated bioelectrical impedance value.

BRIEF DESCRIPTION OF THE FIGURES

The above and other objects and features will become apparent from the following description with reference to the following figures, wherein like reference numerals refer to like parts throughout the various figures unless otherwise specified, and wherein:

FIG. 1 is a block diagram illustrating a configuration of a bio-signal detecting system according to an example embodiment of the inventive concepts;

FIG. 2 is a block diagram illustrating an example configuration of a bio-signal detecting device ofFIG. 1;

FIG. 3 is a graph illustrating changes in bioelectrical impedance measured over time;

FIGS. 4 and 5 are graphs illustrating a process of measuring bioelectrical impedance and estimating a settled bioelectrical impedance value at a bio-processor ofFIG. 2;

FIG. 6 is a block diagram illustrating an example configuration of a digital signal processor ofFIG. 2;

FIG. 7 is a block diagram illustrating another example configuration of a bio-signal detecting device ofFIG. 1;

FIG. 8 is a graph illustrating a process of estimating a settled bioelectrical impedance value depending on bioelectrical impedance and electric skin resistance at a bio-processor ofFIG. 7;

FIG. 9 is a flowchart illustrating an operation method of a bio-processor according to an example embodiment of the inventive concepts;

FIG. 10 is a block diagram illustrating a configuration of a bio-signal detecting system according to an example embodiment of the inventive concepts;

FIG. 11 is a block diagram illustrating a configuration of a bio-signal detecting system according to an example embodiment of the inventive concepts; and

FIG. 12 is a drawing illustrating a configuration of a wearable device according to an example embodiment of the inventive concepts.

DETAILED DESCRIPTION

Hereinafter, some example embodiments of the inventive concepts are described for clarity and in detail so that this disclosure will be thorough and complete and will fully convey the scope of example embodiments the inventive concepts to those skilled in the art.

FIG. 1 is a block diagram illustrating a configuration of a bio-signal detecting system according to an example embodiment of the inventive concepts.

Referring toFIG. 1, abio-signal detecting system100 may include, but is not limited to, a wearable device. For example, thebio-signal detecting system100 may include various portable electronic devices.

Thebio-signal detecting system100 may include abio-signal detecting device110, anapplication processor140, a display driver integrated circuit (DDI)150, adisplay160, astorage device170, amemory180, and amodem190.

Thebio-signal detecting device110 may include anelectrode unit120 and abio-processor130. Theelectrode unit120 may include a plurality of electrodes. The plurality of electrodes may be configured to be in contact with a user to sense a bio-signal. For example, some of the plurality of electrodes may supply an output current to the user, and the other electrodes may receive a sensing voltage from the user. Hereinafter, a target which is in contact with theelectrode unit120 may be called a user. However, example embodiments are not limited thereto. For example, the target which is in contact with theelectrode unit120 may include a variety of objects such as an animal.

Thebio-processor130 may receive a bio-signal from theelectrode unit120 and may analyze the received bio-signal. For example, thebio-processor130 may receive a sensing voltage from theelectrode unit120. Thebio-processor130 may measure bioelectrical impedance based on the sensing voltage and the output current supplied to theelectrode unit120. Thebio-processor130 may generate bio-data based on the measured bioelectrical impedance. For example, the bio-data may be body fat data. Thebio-processor130 may use user data for a height, a weight, an age, and/or a gender of a user to generate the body fat data. Such user data may be stored (e.g., in advance) in thebio-processor130.

Thebio-processor130 may determine a sensing time for measuring bioelectrical impedance. Thebio-processor130 may measure bioelectrical impedance based on a sensing voltage received during the sensing time. If the sensing time is long, a time when motion of the user is limited may be increased. Thus, thebio-processor130 according to an example embodiment of the inventive concepts may reduce (or, alternatively, minimize) a sensing time and may measure bioelectrical impedance based on the sensing voltage gathered during the reduced (or, alternatively, the minimized) sensing time. Herein, thebio-processor130 may perform a processing operation of compensating a decrease in accuracy of a bioelectrical impedance value according to the reduced (or, alternatively, the minimized) sensing time. Such a processing time will be described in detail with reference toFIG. 2.

Thebio-processor130 may perform a function of measuring bioelectrical impedance and a function of generating bio-data, such as body fat data, depending on the bioelectrical impedance in an integrated manner. Thebio-processor130 may directly analyze bioelectrical impedance and may output the analyzed result to theapplication processor140. In this case, compared with outputting data for bioelectrical impedance and user data to theapplication processor140, an amount of data output from thebio-processor130 may be reduced. Further, compared with analyzing bio-data based on bioelectrical impedance at a separate host device (not shown), an amount of data transmitted to the host device through themodem190 may be reduced.

Theapplication processor140 may perform a control operation of controlling thebio-signal detecting system100 and an arithmetic operation of calculating various data. Theapplication processor140 may execute an operating system (OS) and various applications. For example, theapplication processor140 may provide query data for measuring, compensating, and analyzing bioelectrical impedance, and may provide user data for generating bio-data to thebio-processor130. Herein, example embodiments are not limited thereto. For example, the bio-processor130 may measure and compensate bioelectrical impedance. Theapplication processor140 may generate bio-data, such as body fat data, based on the compensated bioelectrical impedance.

TheDDI150 may receive image data based on bio-data analyzed by the bio-processor130 or theapplication processor140. For example, theapplication processor140 may generate image data for displaying information associated with the analyzed bio-data. TheDDI150 may convert the image data into an image data voltage suitable for a specification of thedisplay160. TheDDI150 may output a gray scale voltage according to the image data as an image data voltage.

Thedisplay160 may display information associated with bio-data. Thedisplay160 may receive an image data voltage from the DDI and may display information associated with bio-data, such as body fat data, based on the image data voltage. Thedisplay160 may include a liquid crystal display (LCD), an organic light emitting diode (OLED), an active matrix OLED (AMOLED), a flexible display, an electronic ink, or the like.

Thestorage device170 may be used as an auxiliary memory of theapplication processor140. Source codes of an OS or various applications executed by theapplication processor140 and various data generated to be stored for a long time by the OS or the applications may be stored in thestorage device170. For example, execution codes for measuring or analyzing bioelectrical impedance, user data for calculating bio-data, or the like may be stored in thestorage device170. Thestorage device170 may include a flash memory, a phase-change random access memory (PRAM), a magnetic RAM (MRAM), a ferroelectric RAM (FeRAM), a resistive RAM (RRAM), or the like.

Thememory180 may be used as a main memory of theapplication processor140. For example, thememory180 may store various data and process codes processed by theapplication processor140. For example, measured bioelectrical impedance data, compensated bioelectrical impedance data, or bio-data may be stored in thememory180. Thememory180 may include a dynamic RAM (DRAM), a static RAM (SRAM), a PRAM, an MRAM, an FeRAM, an RRAM, or the like.

Themodem190 may communicate with an external device, for example, a host device (not shown). For example, themodem190 may transmit bio-data, received from theapplication processor140, to the host device. Themodem190 may perform communication based on at least one of various wireless communication schemes, such as long term evolution (LTE), code division multiple access (CDMA), Bluetooth, near field communication (NFC), wireless-fidelity (Wi-Fi), and radio frequency identification (RFID), and various wired communication schemes, such as a universal serial bus (USB), serial AT attachment (SATA), a serial peripheral interface (SPI), an inter-integrated circuit (I2C), a high speed-I2C (HS-I2C), and an integrated-interchip sound (I2S).

FIG. 2 is a block diagram illustrating an example configuration of a bio-signal detecting device ofFIG. 1.

Referring toFIG. 2, a bio-signal detectingdevice110 may include theelectrode unit120 and the bio-processor130.

Theelectrode unit120 may include electrodes. InFIG. 2, an example embodiment is illustrated in which theelectrode unit120 includes first tofourth electrodes121 to124. However, example embodiments are not limited thereto. For example, theelectrode unit120 may include various numbers of electrodes.

The bio-processor130 may include abioelectrical impedance sensor131, an analog-digital converter (ADC)132, acurrent generator133, adigital signal processor134, and anonvolatile memory135.

In some example embodiments, the bio-processor130 may include processing circuitry and a memory (e.g., the nonvolatile memory135), where the processing circuity is configured to perform the functions of one or more of thebioelectrical impedance sensor131, the analog-digital converter (ADC)132, thecurrent generator133, thedigital signal processor134. In other example embodiments, thebioelectrical impedance sensor131, the analog-digital converter (ADC)132, thecurrent generator133, thedigital signal processor134 may each include discrete processing circuity circuits.

The processing circuitry may be, but not limited to, a processor, Central Processing Unit (CPU), a controller, an arithmetic logic unit (ALU), a digital signal processor, a microcomputer, a field programmable gate array (FPGA), an Application Specific Integrated Circuit (ASIC), a System-on-Chip (SoC), a programmable logic unit, a microprocessor, or any other device capable of performing operations in a defined manner.

As discussed in more detail below, the processing circuity may be configured, through a layout design or execution of computer readable instructions stored in the memory (not shown), as a special purpose computer to measure a measured bioelectrical impedance during a sensing time such that the sensing time includes only a portion of a settling time prior to the measured bioelectrical impedance reaching a settled bioelectrical impedance value, estimate the settled bioelectrical impedance value based on changes in the measured bioelectrical impedance, and generate bio-data based on the settled bioelectrical impedance value. Therefore, the processing circuitry may improve the functioning of the bio-processor130 itself by reducing an amount of time to generate the bio-data and increasing the accuracy of the generated bio-data.

Theelectrode unit120 may receive an output current Iout from thecurrent generator133, and supply the output current Iout to a user. For example, the output current Iout may be supplied to the user through thesecond electrode222 and thefourth electrode224. The output current Iout may flow in a body of the user, and a potential difference by resistance of the body of the user may occur. Theelectrode unit120 may receive a sensing voltage Vsen according to such a potential difference and may supply the received sensing voltage Vsen to the bio-processor130. For example, the sensing voltage Vsen may be supplied to the bio-processor130 through thefirst electrode221 and thethird electrode223.

The first tofourth electrodes221 to224 may be configured to be in contact with the user when a bio-signal is measured. For example, thefirst electrode221 and thesecond electrode222 may be configured to be in contact with a left (or right) body of the user, and thethird electrode223 and thefourth electrode224 may be configured to be in contact with a right (or left) body of the user. However, example embodiments are not limited thereto. Thefirst electrode221 and thesecond electrode222 may be located to be adjacent to each other and may be insulated from each other. Thethird electrode223 and thefourth electrode224 may be located to be adjacent to each other and may be insulated from each other. Thesecond electrode222 and thefourth electrode224 may form a closed circuit through the body of the user. Thefirst electrode221 adjacent to thesecond electrode222 and thethird electrode223 adjacent to thefourth electrode224 may supply a potential difference by the output current Iout which flows through the closed circuit, that is, the sensing voltage Vsen to thebioelectrical impedance sensor131.

Thebioelectrical impedance sensor131 may measure bioelectrical impedance of the user based on the sensing voltage Vsen. Thebioelectrical impedance sensor131 may receive the sensing voltage Vsen from theelectrode unit120. Thebioelectrical impedance sensor131 may measure the bioelectrical impedance using the sensing voltage Vsen and the output current Iout. For this purpose, thebioelectrical impedance sensor131 may include a voltmeter. Thebioelectrical impedance sensor131 may measure the bioelectrical impedance using a ratio of the sensing voltage Vsen to the output current Iout.

Thebioelectrical impedance sensor131 may generate a bioelectrical impedance signal BIS based on the measured bioelectrical impedance. For this purpose, thebioelectrical impedance sensor131 may include an analog front end (AFE) (not shown). The AFE may include an amplifier (not shown) for amplifying the sensing voltage Vsen supplied from thefirst electrode121 and thethird electrode123, that is, a potential difference between thefirst electrode121 and thethird electrode123. The AFE may include a band filter for removing a noise of the amplified sensing voltage. A bandwidth of the band filter may be set based on a frequency of the output current Iout supplied from thecurrent generator133. Thebioelectrical impedance sensor131 may generate the bioelectrical impedance signal BIS by amplifying and filtering the sensing voltage Vsen.

Thebioelectrical impedance sensor131 may measure bioelectrical impedance during a sensing time that is set (or, alternatively, may be preset). Theelectrode unit120 may be in contact with the user, and, when such a contact state is maintained, the sensing time when bioelectrical impedance is measured may be classified as including one or more of a floating time, a settling time, or a settled time. The floating time may be defined as a time before the user comes into contact with theelectrode unit120. The settling time may be defined as a time between a time when the user comes into contact with theelectrode unit120 and a time when bioelectrical impedance indicates a desired (or, alternatively, a predetermined) value. The settled time may be defined as a time when bioelectrical impedance indicates a desired (or, alternatively, a predetermined) value or a desired (or, alternatively, a predetermined) range. As discussed below, in one or more example embodiments, the sensing time may include a portion of the settling time.

The settling time may be determined according to various factors, for example, a size of each of the first tofourth electrodes121 to124, a shape of each of the first tofourth electrodes121 to124, an attitude of the user, or an internal characteristic of the user. If a bio-signal detectingsystem100 ofFIG. 1 is implemented as a small wearable device, each of the first tofourth electrodes121 to124 may be small in size. As each of the first tofourth electrodes121 to124 decreases in size, a settling time may increase.

Thebioelectrical impedance sensor131 may measure a bioelectrical impedance signal during a portion of a settling time without also measuring the bioelectrical impedance during the settled time. As will be described below, since the bio-processor130 estimates settled bioelectrical impedance based on measured bioelectrical impedance without waiting until the settled time, the bio-processor130 may quickly generate bio-data. A description will be given of detailed contents with reference toFIG. 3.

TheADC132 may convert the bioelectrical impedance signal BIS into bioelectrical impedance data BID. TheADC132 may receive the bioelectrical impedance signal BIS which is an analog signal from thebioelectrical impedance sensor131. TheADC132 may convert the bioelectrical impedance signal BIS into the bioelectrical impedance data BID which is a digital signal and may output the converted bioelectrical impedance data BID to thedigital signal processor134.

Thecurrent generator133 may generate the output current Iout for measuring bioelectrical impedance. Thecurrent generator133 may supply the output current Iout to theelectrode unit120. Thecurrent generator133 may supply the output current Iout to theelectrode unit120 under control of thedigital signal processor134. Thecurrent generator133 may generate the output current Iout based on a current control signal CCS provided from thedigital signal processor134. The output current Iout may be an alternating current (AC) having a level which is harmless to humans. For example, the output current Iout may be, but is not limited to, a microcurrent having a frequency of 50 KHz.

Thedigital signal processor134 may estimate a settled bioelectrical impedance value based on measured bioelectrical impedance. Thedigital signal processor134 may receive the bioelectrical impedance data BID from theADC132. The bioelectrical impedance data BID may be generated based on bioelectrical impedance measured during a sensing time that is set relatively short without waiting for the settling time. Therefore, if the settling time is too long such that the sensing time does not include the settled time, the bioelectrical impedance data BID may only include information measured during a portion of the settling time and fail to include information about bioelectrical impedance measured during the settled time.

Thedigital signal processor134 may analyze a pattern of bioelectrical impedance during a sensing time and may estimate a settled bioelectrical impedance value. Thedigital signal processor134 may model changes over a time of measured bioelectrical impedance as a fitting function. For example, the fitting function may be, but is not limited to, a natural logarithmic function. For example, the fitting function may include various functions such as an exponential function. Thedigital signal processor134 may determine a coefficient or a constant of the fitting function based on changes in measured bioelectrical impedance. Thedigital signal processor134 may determine a settled time of bioelectrical impedance based on the determined coefficient or constant of the fitting function. Thedigital signal processor134 may estimate a settled bioelectrical impedance value at the determined settled time.

Thedigital signal processor134 may compare a modeled fitting function with a pattern of measured bioelectrical impedance to determine a contact error. If a contact state between the user and theelectrode unit120 is poor, a real waveform of bioelectrical impedance may be indicated in an unsettled manner. In other words, a difference between a waveform of measured bioelectrical impedance and a modeled fitting function may be greatly indicated. If a result of accumulating a difference between the modeled fitting function and the measured bioelectrical impedance is greater than an error reference value, thedigital signal processor134 may determine that a contact error occurs. In this case, thedigital signal processor134 may control the bio-processor130 to re-measure bioelectrical impedance.

Thedigital signal processor134 may generate bio-data using the settled bioelectrical impedance value. For example, thedigital signal processor134 may apply the settled bioelectrical impedance value to regression data. The regression data may include desired (or, alternatively, predetermined) function information to calculate body fat of the user. Thedigital signal processor134 may generate the bio-data based on a parameter and the settled bioelectrical impedance value. For example, the parameter may further include information about a height, a weight, an age, or a gender of the user. Thedigital signal processor134 may generate bio-data by receiving regression data and user information from thenonvolatile memory135.

Thenonvolatile memory135 may store various data for analyzing bioelectrical impedance and generating bio-data. For example, fitting function data for estimating a settled bioelectrical impedance value may be stored in thenonvolatile memory135. Further, user information and regression data for generating bio-data using an estimated bioelectrical impedance value may be stored in thenonvolatile memory135. Thenonvolatile memory135 may be, but is not limited to, a NAND flash memory. For example, thenonvolatile memory135 may be a NOR flash memory, a PRAM, an MRAM, an RRAM, an FeRAM, or an electrically erasable and programmable read only memory (EEPROM).

FIG. 3 is a graph illustrating changes in bioelectrical impedance measured over time.

Referring toFIG. 3, a horizontal axis may represent the flow of time, and a vertical axis may represent bioelectrical impedance. A bioelectrical impedance value may be indicated by being classified as a floating time, a settling time, or a settled time. For convenience of description, a description will be given ofFIG. 3 with reference to reference numerals ofFIGS. 1 and 2.

The floating time may be defined as a time before a first time point t1. The floating time may indicate a time before a user comes into contact with anelectrode unit120. In other words, the first time point t1 may represent a time when the user starts to be in contact with theelectrode unit120. The user may fail to come into contact with theelectronic device120 during the floating time. Thus, a closed circuit may fail to be formed between the user and theelectrode unit120. During the floating time, bioelectrical impedance measured from abioelectrical impedance sensor131 may have a floating impedance value FI1.

The settling time may be defined as a time between the first time point t1 and a second time point t2. The settling time may indicate a time before bioelectrical impedance is settled after the user comes into contact with theelectrode unit120. In other words, the second time point t2 may indicate a time when bioelectrical impedance is settled. During the settling time, a closed circuit may be formed between the user and theelectrode unit120. Thus, thebioelectrical impedance sensor131 may have an impedance value lower than the floating impedance value FI1. Bioelectrical impedance may be gradually reduced during the settling time, and it may have a settled bioelectrical impedance value SI1 at the second time point t2.

The settled time may be defined as a time after the second time point t2. The settled time may represent a time which is in a settled state, after the settling time passes after the user and theelectrode unit120 are in contact with each other. During the settled time, the closed circuit formed between the user and theelectrode unit120 may be kept. If thebioelectrical impedance sensor131 measures bioelectrical impedance during the settled time, the measured bioelectrical impedance may have the settled bioelectrical impedance value SI1. InFIG. 3, an example embodiment is illustrated in which the settled bioelectrical impedance value SI1 is kept constant. However, example embodiments are not limited thereto. For example, during the settled time, bioelectrical impedance may be formed within a specific range with respect to the settled bioelectrical impedance value SI1.

It may be preferable that the settled bioelectrical impedance value SI1 is used to generate bio-data associated with body composition of the user. Herein, the settled bioelectrical impedance value SI1 may be detected after the second time point t2. In general, if the user remains in contact with theelectrode unit120 during at least the entire duration of the settling time between the first time point t1 and the second time point t2, a bio-processor130 may generate settled bio-data. Herein, if a bio-signal detectingsystem100 is implemented with a small size, theelectrode unit120 may be reduced in size and thus the settling time may be increased. As a contact time between the user and theelectrode unit120 is longer, the user may feel more uncomfortable. There may be a high probability that the user does not come into contact with theelectrode unit120 for the full settling time.

FIGS. 4 and 5 are graphs illustrating a process of measuring bioelectrical impedance and estimating a settled bioelectrical impedance value at a bio-processor ofFIG. 2. Referring toFIGS. 4 and 5, a horizontal axis may represent the flow of time, and a vertical axis may represent bioelectrical impedance. A bioelectrical impedance value may be indicated by being classified as a floating time, a settling time, or a settled time. For convenience of description, a description will be given ofFIGS. 4 and 5 with reference to reference numerals ofFIGS. 1 and 2.

FIG. 4 is a drawing illustrating a method for estimating a settled bioelectrical impedance value when a bioelectrical impedance value is measured during a processing time which is shorter than a settling time.

Referring toFIG. 4, a floating time may be defined as a time before a first time point t1. In the floating time, bioelectrical impedance may have a floating impedance value FI2. A processing time may be defined as a time between the first time point t1 and a third time point t3. A settling time may be defined as a time between the first time point t1 and a fourth time point t4 which is later than a third time t3. A settled time may be after the fourth time point t4. In the settled time, bioelectrical impedance may have a settled bioelectrical impedance value SI2.

The processing time may be a sensing time described with reference toFIG. 2. In other words, the processing time may be a time when abioelectrical impedance sensor131 receives a sensing voltage Vsen and measures bioelectrical impedance. Herein, example embodiments are not limited thereto. For example, the processing time may be a time to estimate a settled bioelectrical impedance value by a bio-processor130 in a time when the bio-processor130 measures bioelectrical impedance. The processing time may be shorter than the settling time. Contrary to being shown inFIG. 4, a start point of the processing time may be a time after the first time point t1. During the processing time, measured bioelectrical impedance may be reduced over time. Herein, since the processing time is shorter than the settling time, a bioelectrical impedance value at the third time point t3 may be different from (e.g., larger than) the settled bioelectrical impedance value SI2.

The bio-processor130 may model changes in bioelectrical impedance between the first time point t1 and the third time point t3 as a fitting function. For example, a fitting function f(t) may be defined as a natural logarithmic function “A*ln(t)+B”. The bio-processor130 may calculate an A value and a B value corresponding to the nearest fitting function to bioelectrical impedance measured during the processing time. For example, the bio-processor130 may extract an A value and a B value in which a difference between a measured bioelectrical impedance value and a fitting function is minimized with respect to time. As the settling time is longer, an absolute value of A may be more reduced. Further, as the settled bioelectrical impedance value SI2 is larger, the B value may be larger.

The bio-processor130 may estimate the settled bioelectrical impedance value SI2 based on a determined fitting function. For example, the bio-processor130 may estimate the value of the bioelectrical impedance at the fourth time point t4 based on the determined fitting function. The bio-processor130 may compensate the settled bioelectrical impedance value SI2 using a value of a fitting function for the fourth time point t4. The bio-processor130 may accumulate and calculate a difference between a measured bioelectrical impedance value and a fitting function to ensure reliability of the fitting function. If the accumulated and calculated result is greater than an error reference value, the bio-processor130 may determine that there is no reliability of measured bioelectrical impedance. In other words, the bio-processor130 may determine that a contact error with a user or the like occurs and may re-measure bioelectrical impedance.

Since the bio-processor130 measures bioelectrical impedance for a portion of the settling time and determines the bioelectrical impedance value SI2, a measurement time of the user may be reduced. In other words, the bio-processor130 according to an example embodiment may not wait to measure bioelectrical impedance until the settled time. Further, since a contact error is determined using an accumulated and calculated error value of bioelectrical impedance for a portion of the settling time, bioelectrical impedance may be measured again before the fourth time point t4 and reliability of the settled bioelectrical impedance value SI2 may increase.

FIG. 5 is a drawing illustrating a method for estimating a settled bioelectrical impedance value when bioelectrical impedance is measured during a processing time which is longer than a settling time.

Referring toFIG. 5, a floating time may be defined as a time before a first time point t1. In the floating time, bioelectrical impedance may have a floating impedance value FI3. A processing time may be defined as a time between the first time point t1 and a third time point t3. A settling time may be defined as a time between the first time point t1 and a fifth time point t5 which is earlier than a third time point t3. A settled time may be defined as being after the third time point t3. In the settled time, bioelectrical impedance may have a settled bioelectrical impedance value SI3.

The processing time may be a sensing time described with reference toFIG. 2. Alternatively, the processing time may be a time to estimate a settled bioelectrical impedance value by the bio-processor130. The processing time may be longer than the settling time. Contrary to being shown inFIG. 5, a start point of the processing time may be a time after the first time point t1. In a time between the first time point t1 and the fifth time point t5 in the processing time, measured bioelectrical impedance may be reduced over time. In a time between the fifth time point t5 and the third time point t3 in the processing time, the measured bioelectrical impedance may arrive at a settled state and may indicate the settled bioelectrical impedance value SI3.

To ensure user convenience, it may be preferable that the bio-processor130 has a processing time which is shorter than a settling time and estimates a settled bioelectrical impedance value before arriving at a settled time. The bio-processor130 may set a processing time or a sensing time which is shorter than a settling time with respect to an average settling time of a general user. Herein, according to an internal characteristic of the user or the like, as shown inFIG. 5, the processing time may be longer than the settling time.

The bio-processor130 may model changes in bioelectrical impedance between the first time point t1 and the third time point t3 as a fitting function. For example, the fitting function may be a natural logarithmic function. As shown inFIG. 4, the bio-processor130 may estimate the settled bioelectrical impedance value SI3 based on a modeled fitting function. The bio-processor130 may determine whether the settling time is shorter than the processing time and if the settled bioelectrical impedance value SI3 is maintained longer than a specified reference time, the bio-processor130 may immediately determine the settled bioelectrical impedance value SI3 without modeling changes in bioelectrical impedance.

FIG. 6 is a block diagram illustrating an example configuration of a digital signal processor ofFIG. 2.

Referring toFIG. 6, adigital signal processor134 may generate bio-data including body fat data BFD. Thedigital signal processor134 may generate bio-data in various manners and is not limited to an embodiment ofFIG. 6.

Thedigital signal processor134 may be configured, through a layout design or execution of computer readable instructions stored in the memory (not shown), as a special purpose computer to perform the functions of one or more of a modeling circuit134_1, an error detecting circuit134_2, an impedance compensation circuit134_3, and a body fat calculating circuit134_4. For convenience of description, a description will be given ofFIG. 6 with reference numerals ofFIG. 2.

The modeling circuit134_1 may model bioelectrical impedance measured during a sensing time or a processing time as a fitting function. The modeling circuit134_1 may receive bioelectrical impedance data BID from anADC132. The modeling circuit134_1 may determine a coefficient or a constant of the fitting function based on the bioelectrical impedance data BID. For example, the modeling circuit134_1 may determine a fitting function as a natural logarithmic function and may determine a coefficient value and a constant value of the nearest natural logarithmic function to changes in a value of the bioelectrical impedance data BID over time. The modeling circuit134_1 may generate modeling data MD based on the determined coefficient value and the determined constant value.

The error detecting circuit134_2 may compare the modeled fitting function with actually measured bioelectrical impedance to determine a contact error by an attitude of a user. The error detecting circuit134_2 may receive the modeling data MD from the modeling circuit134_1. The error detecting circuit134_2 may receive the bioelectrical impedance data BID from theADC132. The error detecting circuit134_2 may compare the modeling data MD with the bioelectrical impedance data BID. The error detecting circuit134_2 may accumulate and calculate a difference value between the modeling data MD and the bioelectrical impedance data BID. If the accumulated and calculated result is greater than an error reference value, the error detecting circuit134_2 may determine that a contact error occurs and may generate error data ED.

Based on the error data ED, thedigital signal processor134 may fail to estimate settled bioelectrical impedance. The error detecting circuit134_2 may provide the error data ED to the modeling circuit134_1. When receiving the error data ED, the modeling circuit134_1 may fail to provide the modeling data MD to the impedance compensation circuit134_3. In this case, thedigital signal processor134 may control a bio-processor130 to measure bioelectrical impedance again without calculating settled bioelectrical impedance. Contrary to being shown inFIG. 6, the error data ED is provided to the impedance compensation circuit134_3 to stop calculating settled bioelectrical impedance, or the error data ED is provided to the body fat calculating circuit134_4 to stop calculating body fat data BFD.

The impedance compensation circuit134_3 may estimate a settled bioelectrical impedance value based on the modeled fitting function. The impedance compensation circuit134_3 may receive the modeling data MD from the modeling circuit134_1. The impedance compensation circuit134_3 may determine a settled time of bioelectrical impedance from the modeling data MD, and an estimated value of the bioelectrical impedance at the settled time. For example, the impedance compensation circuit134_3 may predict a waveform according to a coefficient value and a constant value of a fitting function and may estimate a settled time of bioelectrical impedance depending on the predicted waveform. The impedance compensation circuit134_3 may calculate a value of the fitting function at the settled time to generate settled bioelectrical impedance data SCD.

The body fat calculating circuit134_4 may calculate body fat of the user based on the estimated bioelectrical impedance value. The body fat calculating circuit134_4 may receive the settled bioelectrical impedance data SCD from the impedance compensation circuit134_3. The body fat calculating circuit134_4 may receive user data PD from thenonvolatile memory135 or the application processor140 (seeFIGS. 1 and 2). The user data PD may include information associated with the user. For example, the user data PD may include information indicating a height, a weight, an age, and/or a gender of a user. However, example embodiments are not limited thereto. The body fat calculating circuit134_4 may apply the user data PD and the settled bioelectrical impedance data SCD as parameters to a regression equation. The body fat calculating circuit134_4 may additionally receive data for such a regression equation from thenonvolatile memory135.

The body fat calculating circuit134_4 may generate body fat data BFD by applying various parameters including the settled bioelectrical impedance data SCD to the regression equation. The body fat data BFD may be output according to a request of theapplication processor140 and/or an external host device. In this case, compared with directly processing the bioelectrical impedance data BID and calculating body fat data BFD at theapplication processor140 or the external host device, by calculating the body fat data BFD at thebio processor130 an amount of transmitted data may be reduced and power consumption according to data transmission may be reduced.

FIG. 7 is a block diagram illustrating another example configuration of a bio-signal detecting device ofFIG. 1. A bio-signal detectingdevice210 may be a bio-signal detectingdevice110 ofFIG. 1.

Referring toFIG. 7, thebio-signal detecting device210 may include anelectrode unit220 and a bio-processor230.

The bio-processor230 may include abioelectrical impedance sensor231, a Galvanicskin response sensor232, anADC233, acurrent generator234, adigital signal processor235, and anonvolatile memory236.

Theelectrode unit220 may include first tofourth electrodes221 to224. Theelectrode unit220 may supply a first output current Iout1 and a second output current Iout2, received from thecurrent generator234, to a user. Thesecond electrode222 may supply the first output current Iout1 to the user, and thefourth electrode224 may supply the second output current Iout2 to the user. As theelectrode unit220 supplies the first output current Iout1 and the second output current Iout2 to the user, it may receive a generated first sensing voltage Vsen1 and a generated second sensing voltage Vsen2 and may supply the first sensing voltage Vsen1 and the second sensing voltage Vsen2 to thebioelectrical impedance sensor231. Thefirst electrode221 may supply the first sensing voltage Vsen1 to thebioelectrical impedance sensor231, and thethird electrode223 may supply the second sensing voltage Vsen2 to thebioelectrical impedance sensor231. The process of supplying an output current to the user to measure bioelectrical impedance and supplying a sensing voltage to the bio-processor230 at the first tofourth electrodes221 to224 may be the same as that inFIG. 2.

Theelectrode unit220 may receive a first Galvanic voltage Vgsr1 and a second Galvanic voltage Vgsr2 and may supply the first Galvanic voltage Vgsr1 and the second Galvanic voltage Vgsr2 to the Galvanicskin response sensor232 to measure electric skin resistance by a Galvanic skin response. An operation of theelectrode unit220 for measuring bioelectrical impedance and an operation of theelectrode unit220 for measuring electric skin resistance by a Galvanic skin response may be generated in a different time. To measure electric skin resistance, it may be assumed that thethird electrode223 and thefourth electrode224 are used. Thethird electrode223 and thefourth electrode224 may be located to be adjacent to each other and may be insulated from each other.

Thethird electrode223 and thefourth electrode224 may receive a direct current (DC) from thecurrent generator234 and may supply the received DC to the user. In this case, resistance between thethird electrode223 and thefourth electrode224 through the user may be changed by a Galvanic skin response. The Galvanic skin response may be indicated based on states of sweat glands. A potential difference may be formed between thethird electrode223 and thefourth electrode224 based on the changed resistance. Thethird electrode223 may receive the first Galvanic voltage Vgsr1 and may supply the first Galvanic voltage Vgsr1 to the Galvanicskin response sensor232, and thefourth electrode224 may receive the second Galvanic voltage Vgsr2 and may supply the second Galvanic voltage Vgsr2 to the Galvanicskin response sensor232.

Thebioelectrical impedance sensor231 may measure bioelectrical impedance of the user based on the first sensing voltage Vsen1 and the second sensing voltage Vsen2. Thebioelectrical impedance sensor231 may generate a bioelectrical impedance signal BIS based on the measured bioelectrical impedance. Since a configuration and function of thebioelectrical impedance sensor231 is the same as that of abioelectrical impedance sensor131 ofFIG. 2, a detailed description will be omitted.

The Galvanicskin response sensor232 may measure electric skin resistance of the user based on the first Galvanic voltage Vgsr1 and the second Galvanic voltage Vgsr2. The Galvanicskin response sensor232 may sense changes in resistance using the first Galvanic voltage Vgsr1 and the second Galvanic voltage Vgsr2. For this purpose, the Galvanicskin response sensor232 may include a voltmeter. The Galvanicskin response sensor232 may measure changes in resistance according to a change in the first Galvanic voltage Vgsr1 and the second Galvanic voltage Vgsr2.

The Galvanicskin response sensor232 may generate a Galvanic skin response signal GSS based on the measured electric skin resistance. For this purpose, the Galvanicskin response sensor232 may include an AFE (not shown). The AFE may include an amplifier (not shown) for amplifying a potential difference between the first Galvanic voltage Vgsr1 and the second Galvanic voltage Vgsr2. The AFE may include a low pass filter (LPF) for removing a noise of an amplified Galvanic voltage.

The Galvanicskin response sensor232 may measure electric skin resistance before a sensing time for measuring bioelectrical impedance. In other words, after the Galvanicskin response sensor232 measures the electric skin resistance, thebioelectrical impedance sensor231 may measure bioelectrical impedance. InFIG. 7, an example embodiment illustrates that the Galvanicskin response sensor232 and thebioelectrical impedance sensor231 are independent of each other. However, example embodiments are not limited thereto. For example, the Galvanicskin response sensor232 and thebioelectrical impedance sensor231 may be integrated into one configuration.

TheADC233 may convert the bioelectrical impedance signal BIS into bioelectrical impedance data BID. TheADC233 may convert the Galvanic skin response signal GSS into Galvanic skin response data GSD. Since a configuration and function of theADC233 is the same as that of anADC132 ofFIG. 2, a detailed description will be omitted.

Thecurrent generator234 may generate the first output current Iout1 and the second output current Iout2 for measuring bioelectrical impedance. Thecurrent generator234 may supply the first output current Iout1 to thesecond electrode222 and may supply the second output current Iout2 to thefourth electrode224. Thecurrent generator234 may generate a DC for measuring electric skin resistance. Thecurrent generator234 may supply the DC to thethird electrode223 or thefourth electrode224. Thecurrent generator234 may generate the first and second output currents Iout1 and Iout2 or may generate the DC, based on a current control signal CSS.

Thedigital signal processor235 may estimate a settled bioelectrical impedance value based on measured bioelectrical impedance. Since a process of estimating the settled bioelectrical impedance value is the same as that described with reference toFIG. 2, a detailed description will be omitted. Thedigital signal processor235 may compensate a settled bioelectrical impedance value based on additionally measured electric skin resistance. For example, thedigital signal processor235 may estimate a contact resistance value at a time where bioelectrical impedance is settled, based on the measured electric skin resistance. Herein, contact resistance may refer to resistance by a contact between a user and theelectrode unit220, in which a degree of skin dryness by sweat or the like is reflected. Thedigital signal processor235 may use a contact resistance value as a parameter of regression data to compensate the contact resistance value for an estimated bioelectrical impedance value.

Thedigital signal processor235 may predict a settling time of bioelectrical impedance based on measured electric skin resistance and measured bioelectrical impedance. Thedigital signal processor235 may analyze a pattern of bioelectrical impedance measured during a sensing time and may model the analyzed pattern as a fitting function. Thedigital signal processor235 may reflect electric skin resistance measured in the process of modeling the fitting function. In other words, thedigital signal processor235 may determine a coefficient and a constant of the fitting function based on measured electric skin resistance and measured bioelectrical impedance. Herein, example embodiments are not limited thereto. For example, thedigital signal processor235 may model a fitting function based on measured bioelectrical impedance and may predict a settling time to estimate a settled bioelectrical impedance value, thus reflecting measured electric skin resistance to compensate a bioelectrical impedance value.

Thedigital signal processor235 may predict a contact time between theelectrode unit220 and the user based on measured electric skin resistance. For example, if a bio-signal detectingsystem100 is implemented as a wearable device, the wearable device may have already been already worn prior to the present iteration of measuring the bioelectrical impedance. Thedigital signal processor235 may predict a time when the wearable device is worn, depending on states of sweat glands of the user based on measured electric skin resistance. Thedigital signal processor235 may model electric skin resistance according to the time when the wearable device is worn and may predict a contact resistance value at a time when bioelectrical impedance is settled. Thedigital signal processor235 may compensate a settled bioelectrical impedance value by reflecting the predicted contact resistance value.

FIG. 8 is a graph illustrating a process of estimating a settled bioelectrical impedance value depending on bioelectrical impedance and electric skin resistance at a bio-processor ofFIG. 7.

Referring toFIG. 8, a horizontal axis may represent the flow of time, and a vertical axis may represent resistance. A bioelectrical impedance value may be indicated by being classified as a floating time, a settling time, or a settled time. For convenience of description, a description will be given ofFIG. 8 with reference to reference numerals ofFIG. 7.

A dotted line ofFIG. 8 indicates changes in measured bioelectrical impedance if a user sweats more than a general person. An alternate long and short dash line ofFIG. 8 indicates changes in measured bioelectrical impedance if the user has a drier skin than a general person. A solid line of theFIG. 8 indicates changes in bioelectrical impedance which compensates a change in contact resistance according to a degree of skin dryness. The solid line, the dotted line, and the alternate long and short dash line shown inFIG. 8 may be understood as a graph simplified for convenience of description. A real degree of skin dryness may be changed in real time by stress or external stimulation.

Referring toFIG. 8, a floating time may be defined as a time before a first time point t1. In the floating time, bioelectrical impedance may have a floating impedance value FI4. Further, on a structure of a wearable device, athird electrode223 and afourth electrode224 may maintain a state where thethird electrode223 and thefourth electrode224 are in contact with the user, and afirst electrode221 and asecond electrode222 may be additionally in contact with the user when measuring bioelectrical impedance. As a contact time between the user and thethird electrode223 and thefourth electrode224 is longer, the user may sweat a lot more. As the user sweat a lot more, since water or electrolyte having electrical conductivity is more generated, electric skin resistance may be reduced. Thus, electric skin resistance may continue being reduced during a floating time.

A settling time may be defined as a time between a first time point t1 and a sixth time point t6. A processing time may be defined as a time between the first time point t1 and a third time point t3 which is earlier than the sixth time point t6. Bioelectrical impedance may be reduced during the settling time. In case of a person who sweats a lot, as shown by a dotted line, electric skin resistance may be rapidly reduced. In case of a person who sweats a little, as shown by an alternate long and short dash line, electric skin resistance may be relatively gently reduced. As described above, during the processing time, abioelectrical impedance sensor231 may model changes in bioelectrical impedance as a fitting function. Thebioelectrical impedance sensor231 may estimate a bioelectrical impedance value at the sixth time point t6 based on the modeled fitting function.

In case of a person who sweats a lot, an estimated bioelectrical impedance value may indicate a first bioelectrical impedance value GIa. In case of a person who sweats a little, an estimated bioelectrical impedance value may indicate a second bioelectrical impedance value GIb.

As described above, the Galvanicskin response sensor232 may measure electric skin resistance before bioelectrical impedance is measured. thedigital signal processor235 may predict a contact time between anelectrode unit222 and a user based on the measured electric skin resistance. Thedigital signal processor235 may predict electric skin resistance at the sixth time point t6 based on the predicted contact time. Thedigital signal processor235 may compensate the first bioelectrical impedance value GIa or the second bioelectrical impedance value GIb to a compensated bioelectrical impedance value SI4 based on the electric skin resistance at the sixth time point t6.

Thedigital signal processor235 may compensate the first bioelectrical impedance value GIa and/or the second bioelectrical impedance value GIb in a process of generating bio-data. For example, thedigital signal processor235 may compensate the measured first bioelectrical impedance value GIa and/or the measured second bioelectrical impedance value GIb to the compensated bioelectrical impedance value SI4 by using an electric skin resistance value determined by the Galvanicskin response sensor232 as a parameter of regression data.

Thedigital signal processor235 may compensate the first bioelectrical impedance value GIa and/or the second bioelectrical impedance value GIb to the compensated bioelectrical impedance value SI4 in a process of estimating a settled bioelectrical impedance value. For example, thedigital signal processor235 may model changes in bioelectrical impedance and may calculate a fitting function corresponding to a dotted line or an alternate long and short dash line, thus compensating the calculated fitting function to a fitting function corresponding to a solid line based on measured electric skin resistance. Alternatively, thedigital signal processor235 may model changes in bioelectrical impedance and may determine the first bioelectrical impedance value GIa and/or the second bioelectrical impedance value GIb as a settled bioelectrical impedance value, thus determining a final bioelectrical impedance value as the compensated bioelectrical impedance value SI4.

FIG. 9 is a flowchart illustrating an operation method of a bio-processor according to an example embodiment of the inventive concepts.

Referring toFIG. 9, the operation method of the bio-processor may be performed by a bio-processor130 ofFIG. 1 or 2 or a bio-processor230 ofFIG. 7. For convenience of description, a description will be given ofFIG. 9 with reference to reference numerals ofFIG. 2.

In operation S110, thebioelectrical impedance sensor131 may measure a sensing voltage during a sensing time. Thebioelectrical impedance sensor131 may receive a sensing voltage Vsen from anelectrode unit120. Thebioelectrical impedance sensor131 may measure bioelectrical impedance for the user using an output current Iout supplied to a user and the sensing voltage Vsen supplied from the user. The sensing time may include a portion of a settling time. Thedigital signal processing134 may control the length of the sensing time such that the sensing time may be shorter than the settling time.

In operation S120, thedigital signal processor134 may model bioelectrical impedance. Thedigital signal processor134 may model bioelectrical impedance measured during the sensing time as a fitting function. The fitting function may be a function which has linearity over time, for example, a natural logarithmic function. The fitting function may indicate an approximate value of bioelectrical impedance at the settling time. Thedigital signal processor134 may determine a coefficient or a constant of a fitting function having the nearest value to a value of measured bioelectrical impedance.

In operation S130, thedigital signal processor134 may determine a contact error. Thedigital signal processor134 may compare the modeled fitting function with measured bioelectrical impedance. Thedigital signal processor134 may accumulate and calculate a difference between the fitting function and real bioelectrical impedance at a corresponding time. If the accumulated and calculated result is greater than an error reference value, thedigital signal processor134 may determine that a contact error occurs between the user and anelectrode unit120. If the contact error is detected, a bio-signal detectingsystem100 may provide a visual or auditory message for requesting to maintain a contact state with theelectrode unit120 to the user. Thereafter, operation S110 may progress again. If the contact error is not detected, operation S140 may progress.

In operation S140, thedigital signal processor134 may estimate a settled bioelectrical impedance value. Thedigital signal processor134 may estimate the settled bioelectrical impedance value based on the fitting function modeled in operation S120. For example, thedigital signal processor134 may determine a settled time of a bioelectrical impedance value based on the modeled fitting function. Thedigital signal processor134 may estimate a fitting function value of the settled time as the settled bioelectrical impedance value.

As shown inFIG. 7, if the bio-processor230 includes a Galvanicskin response sensor232, in operation5140, contact resistance of a settled time, calculated as a result of measuring electric skin resistance, may be reflected in a settled bioelectrical impedance value. In other words, thedigital signal processor235 ofFIG. 7 may calculate a contact resistance value between the user and theelectrode unit220 based on electric skin resistance measured by the Galvanicskin response sensor232. Thedigital signal processor235 may reflect a contact resistance value in the settled bioelectrical impedance value to remove additional resistance generated by sweat or the like.

In operation5150, thedigital signal processor134 may calculate body fat based on the estimated bioelectrical impedance value. Thedigital signal processor134 may apply the estimated bioelectrical impedance value to a regression equation to calculate the body fat. Thedigital signal processor134 may additionally apply user information about a height, a weight, an age, or a gender as well as the bioelectrical impedance to the regression equation to calculate the body fat. The user information and information about the regression equation may be previously stored in anonvolatile memory135.Operation150 is specified to calculate the body fat. However, example embodiments are not limited thereto. For example, thedigital signal processor134 may calculate a variety of body composition based on the settled bioelectrical impedance value.

FIG. 10 is a block diagram illustrating a configuration of a bio-signal detecting system according to an example embodiments of the inventive concepts. A bio-signal detectingsystem100 ofFIG. 1 may process a process of sensing bioelectrical impedance and generating bio-data based on the sensed bioelectrical impedance in an integrated manner using a bio-processor130. A bio-signal detectingsystem300 ofFIG. 10 may separately provide a configuration of sensing bioelectrical impedance and a configuration of generating bio-data based on the bioelectrical impedance.

Referring toFIG. 10, thebio-signal detecting system300 may include a bio-signal detectingdevice310 and ahost device360. Thebio-signal detecting device310 may include anelectrode unit320, abioelectrical impedance sensor330, aprocessor340, and ahost interface350. Since theelectrode unit320 has the same configuration as anelectrode unit120 ofFIG. 1 and performs the same function as theelectrode unit120, a detailed description will be omitted.

Thebioelectrical impedance sensor330 may measure bioelectrical impedance during a sensing time. Thebioelectrical impedance sensor330 may supply an output current to a user through theelectrode unit320. For this purpose, thebioelectrical impedance sensor330 may include a current generator. Thebioelectrical impedance sensor330 may receive a sensing voltage generated by the output current through the user, via theelectrode unit320. Thebioelectrical impedance sensor330 may measure bioelectrical impedance for the user based on the received sensing voltage. Thebioelectrical impedance sensor330 may perform the same function as abioelectrical impedance sensor131 ofFIG. 2.

Theprocessor340 may estimate a settled bioelectrical impedance value based on bioelectrical impedance measured during a sensing time. Theprocessor340 may model bioelectrical impedance measured during the sensing time as a fitting function. Theprocessor340 may determine a coefficient or a constant of the fitting function to be nearest to measured bioelectrical impedance. Theprocessor340 may estimate a bioelectrical impedance value of a settled time based on a determined fitting function. Further, theprocessor340 may compare the fitting function with the measured bioelectrical impedance to determine a contact error. The operation of estimating the settled bioelectrical impedance value of theprocessor340 may be the same as that of adigital signal processor134 ofFIG. 2.

Theprocessor340 may generate bio-data based on the estimated bioelectrical impedance value. Theprocessor340 may apply a settled bioelectrical impedance value to regression data. Theprocessor340 may apply a parameter including a settled bioelectrical impedance value and user data to the regression data to generate bio-data. The user data may be received from thehost device360 through thehost interface350. Theprocessor340 may provide bio-data to thehost device360 through thehost interface350 depending on a request of thehost device360. The process of generating the bio-data at theprocessor340 may be the same as that of adigital signal processor134 ofFIG. 2.

Thehost interface350 may provide an interface between thehost device360 and thebio-signal detecting device310. Thehost interface350 may communicate with thehost device360 using a universal serial bus (USB), a small computer system interface (SCSI), a peripheral component interconnect (PCI) express, ATA, parallel ATA (PATA), serial ATA (SATA), a serial attached SCSI (SAS), or the like.

Thehost device360 may communicate with thebio-signal detecting device310 through thehost interface350. Thehost device360 may provide query data for requesting to provide bio-data to thebio-signal detecting device310. In this case, thehost device360 may receive the bio-data from thebio-signal detecting device310. For this purpose, thehost device360 may provide user data to thebio-signal detecting device310. Thehost device360 may include various electronic devices such as a computer device, a smartphone, or a portable terminal.

FIG. 11 is a block diagram illustrating a configuration of a bio-signal detecting system according to an example embodiment of the inventive concepts.

Referring toFIG. 11, a bio-signal detectingsystem400 ofFIG. 11 may separately provide a configuration of sensing bioelectrical impedance and a configuration of generating bio-data based on the bioelectrical impedance.

Thebio-signal detecting system400 may include a bio-signal detectingdevice410 and ahost device450. Thebio-signal detecting device410 may include anelectrode unit420, abioelectrical impedance sensor430, and ahost interface440. Thehost device450 may include aprocessor460.

Since theelectrode unit420 has the same configuration as anelectrode unit120 ofFIG. 1 or anelectrode320 ofFIG. 10 and performs the same function as theelectrode unit120 or theelectrode320, a detailed description will be omitted. Since thebioelectrical impedance sensor430 has the same configuration as abioelectrical impedance sensor330 ofFIG. 10 and performs the same function as thebioelectrical impedance sensor330, a detailed configuration will be omitted. Thehost interface440 may have the same configuration as ahost interface350 ofFIG. 10 and may perform the same function as thehost interface350. Thehost interface440 may transmit information about bioelectrical impedance measured during a sensing time by thebioelectrical impedance sensor430 to thehost device450.

Thehost device450 may communicate with thebio-signal detecting device410 through thehost interface440. Thehost device450 may provide query data for requesting to provide bioelectrical impedance information to thebio-signal detecting device410. In this case, thehost device450 may receive the bioelectrical impedance information from thebio-signal detecting device410.

Theprocessor460 may estimate a settled bioelectrical impedance value based on the bioelectrical impedance information received from thebio-signal detecting device410. Theprocessor460 may model bioelectrical impedance measured by thebioelectrical impedance sensor430 as a fitting function. Theprocessor460 may estimate a bioelectrical impedance value of a settled time based on the fitting function. Theprocessor460 may generate bio-data based on a settled bioelectrical impedance value. Theprocessor460 may perform the same function as aprocessor340 ofFIG. 10 or adigital signal processor134 ofFIG. 2.

FIG. 12 is a drawing illustrating a configuration of a wearable device according to an example embodiment of the inventive concepts.

Referring toFIG. 12, awearable device500 ofFIG. 12 may be configured to be worn on a wrist of a user. A bio-signal detectingsystem100 ofFIG. 1 may be implemented in thewearable device500 ofFIG. 12. Alternatively, a bio-signal detectingdevice310 ofFIG. 10 or a bio-signal detectingdevice410 ofFIG. 11 may be implemented in thewearable device500.

Thewearable device500 may include aprocessor510, anelectrode unit520, and adisplay560.

Theprocessor510 may be embedded in thewearable device500. Theprocessor510 may measure bioelectrical impedance and may generate bio-data. In this case, theprocessor510 may be, but is not limited to, a bio-processor130 ofFIG. 2 or a bio-processor230 ofFIG. 7. For example, theprocessor510 may estimate a settled bioelectrical impedance value based on measured bioelectrical impedance and may generate bio-data. In this case, theprocessor510 may be aprocessor340 ofFIG. 10, and thewearable device500 may separately include a bioelectrical impedance sensor.

Theelectrode unit520 may include first tofourth electrodes521 to524. Thefirst electrode521 and thesecond electrode522 may be located to be adjacent to a display surface of thedisplay560 included in thewearable device500. In other words, thefirst electrode521 and thesecond electrode522 may fail to be in contact with the wrist when the user wears thewearable device500. Thefirst electrode521 and thesecond electrode522 may be located to be adjacent to each other and may be insulated from each other. Thethird electrode523 and thefourth electrode524 may be located on a contact surface of the wrist with thewearable device500. In other words, thethird electrode523 and thefourth electrode524 may be in contact with the wrist when the user wears thewearable device500. Thethird electrode523 and thefourth electrode524 may be located to be adjacent to each other and may be insulated from each other.

If thewearable device500 is worn on a left wrist of the user, to measure bioelectrical impedance, the user brings his or her right hand into contact with thefirst electrode521 and thesecond electrode522. In this case, the second electrode522 (or a first electrode521) and the fourth electrode524 (or the third electrode523) may form a closed circuit through a body of the user. Theprocessor510 may measure bioelectrical impedance using a potential difference by an output current which flows via the closed circuit, for example, a sensing voltage.

Thedisplay560 may display information associated with bio-data generated according to measured bioelectrical impedance. Further, if a contact state between the user and theelectrode unit520 is bad as the determined result of theprocessor510, thedisplay560 may display a message for requesting the user to maintain a contact state with theelectrode unit520. Thewearable device500 may further include a speaker (not shown) for auditorily providing information associated with bio-data or a message for requesting to maintain a contact state.

Although not illustrated in detail, thewearable device500 may further include various elements for measuring bioelectrical impedance and generating, displaying, and transmitting bio-data such as body fat data. For example, thewearable device500 may further include aprocessor140, astorage device170, amemory180, and a modem ofFIG. 1.

The bio-processor, the bio-signal detecting system, and an operation method of the bio-processor may reduce a time when a bio-signal is measured, by estimating a settled bioelectrical impedance value based on bioelectrical impedance of a settling time, thus ensuring accuracy of the settled bioelectrical impedance value.

While the inventive concepts have been described with reference to some example embodiments, it will be apparent to those skilled in the art that various changes and modifications may be made without departing from the spirit and scope of the inventive concepts. Therefore, it should be understood that the above example embodiments are not limiting, but illustrative.

Claims (18)

What is claimed is:

1. A bio-processor, comprising:

a bioelectrical impedance sensor electrically connected to electrodes, the bioelectrical impedance sensor configured to measure changes in bioelectrical impedance by sensing a sensing voltage to generate a measured bioelectrical impedance; and

a digital signal processor configured to,

estimate, during a settling time, a settled bioelectrical impedance value corresponding to a settled time after expiration of the settling time by,

measuring, via the bioelectrical impedance sensor, the measured bioelectrical impedance during a sensing time corresponding to a portion of the settling time shorter than an entirety of the settling time, the settling time being prior to the measured bioelectrical impedance reaching the settled bioelectrical impedance value at the settled time, and

compensating for the sensing time being shorter than the entirety of the settling time by digitally modeling the value of the measured bioelectrical impedance for the settling time in a fitting function based on changes in the sensing voltage to generate a modeled fitting function, and estimating the settled bioelectrical impedance value at the settled time based on the modeled fitting function, and

generate bio-data based on the estimated settled bioelectrical impedance value.

2. The bio-processor ofclaim 1, wherein the digital signal processor is configured to:

calculate a time when the measured bioelectrical impedance is settled from the modeled fitting function; and

estimate the settled bioelectrical impedance value based on the time.

3. The bio-processor ofclaim 1, wherein the modeled fitting function is a natural logarithmic function.

4. The bio-processor ofclaim 1, wherein the digital signal processor is configured to:

determine a contact error between the electrodes and a user by comparing the modeled fitting function with the changes in the measured bioelectrical impedance.

5. The bio-processor ofclaim 1, wherein the digital signal processor is configured to:

generate the bio-data based on a parameter included in the settled bioelectrical impedance value such that the bio-data generated by the digital signal processor includes body fat data.

6. The bio-processor ofclaim 5, further comprising:

a nonvolatile memory configured to store parameter data and regression data, the parameter data including information about a value of the parameter and the regression data including data used to calculate the bio-data from the value of the parameter.

7. The bio-processor ofclaim 1, further comprising:

a Galvanic skin response sensor configured to measure an electric skin resistance by a Galvanic skin response before expiration of the settling time,

wherein the digital signal processor is configured to:

estimate a contact resistance value after the settling time based on the electric skin resistance; and

adjust the settled bioelectrical impedance value based on the contact resistance value to generate a compensated settled bioelectrical impedance value.

8. The bio-processor ofclaim 1, wherein the digital signal processor comprises:

a modeling circuit configured to model the changes in the measured bioelectrical impedance in the fitting function to generate the modeled fitting function;

an error detecting circuit configured to generate a contact error data by comparing the modeled fitting function with the changes in the measured bioelectrical impedance; and

an impedance compensation circuit configured to calculate the settled bioelectrical impedance value based on the modeled fitting function.

9. A bio-signal detecting system, the bio-signal detecting system comprising:

an electrode device configured to supply an output current to outside the bio-signal detecting system, and to receive a sensing voltage based on the output current;

a bioelectrical impedance sensor electrically connected to the electrode device, the bioelectrical impedance sensor configured to measure changes in bioelectrical impedance by sensing the sensing voltage to generate a measured bioelectrical impedance; and

a processor configured to,

estimate, during a settling time, a settled bioelectrical impedance value corresponding to a settled time after expiration of the settling time by,

measuring, via the bioelectrical impedance sensor, the measured bioelectrical impedance during a sensing time corresponding to a portion of the settling time shorter than an entirety of the settling time, the settling time being prior to the measured bioelectrical impedance reaching the settled bioelectrical impedance value at the settled time, and

compensating for the sensing time being shorter than the entirety of the settling time by digitally modeling the value of the measured bioelectrical impedance for the settling time in a fitting function based on changes in the sensing voltage to generate a modeled fitting function, and estimating the settled bioelectrical impedance value at the settled time based on the modeled fitting function, and

generate bio-data based on the estimated settled bioelectrical impedance value.

10. The bio-signal detecting system ofclaim 9, wherein the processor is configured to:

output the bio-data through a host interface.

11. The bio-signal detecting system ofclaim 9, wherein the bioelectrical impedance sensor is configured to:

generate a bioelectrical impedance signal based on the sensing voltage; and

output the bioelectrical impedance signal through a host interface, the processor is configured to:

estimate the settled bioelectrical impedance value based on the bioelectrical impedance signal.

12. The bio-signal detecting system ofclaim 9, wherein

the output current includes a first output current and a second output current,

the sensing voltage includes a first sensing voltage and a second sensing voltage, and

the electrode device includes,

a first electrode configured to receive the first sensing voltage;

a second electrode configured adjacent to the first electrode, the second electrode configured to output the first output current;

a third electrode configured to receive the second sensing voltage; and

a fourth electrode configured adjacent to the third electrode, the fourth electrode configured to output the second output current.

13. The bio-signal detecting system ofclaim 12, further comprising:

a Galvanic skin response sensor configured to,

receive a first Galvanic voltage from the third electrode,

receive a second Galvanic voltage from the fourth electrode, and

measure electric skin resistance based on the first Galvanic voltage and the second Galvanic voltage.

14. The bio-signal detecting system ofclaim 9, further comprising:

a Galvanic skin response sensor configured to sense a Galvanic voltage from the electrode device, and to measure electric skin resistance based on the Galvanic voltage,

wherein the processor is configured to:

calculate body fat data based on the settled bioelectrical impedance value; and

adjust the body fat data based on the measured electric skin resistance to generate a compensated settled bioelectrical impedance value.

15. The bio-signal detecting system ofclaim 9, further comprising:

a Galvanic skin response sensor configured to sense a Galvanic voltage from the electrode device, and to measure electric skin resistance based on the Galvanic voltage,

wherein the processor is configured to:

predict the settling time based on the measured electric skin resistance and the changes in the measured bioelectrical impedance to generate a predicted settling time; and

estimate the settled bioelectrical impedance value based on the predicted settling time.

16. The bio-signal detecting system ofclaim 9, further comprising:

a Galvanic skin response sensor configured to sense a Galvanic voltage from the electrode device, and to measure an electric skin resistance based on the Galvanic voltage,

wherein the processor is configured to:

estimate a contact time between the electrode device and a user based on the electric skin resistance; and

estimate the settled bioelectrical impedance value based on the changes in the measured bioelectrical impedance and the contact time.

17. An operation method of a bio-processor, the method comprising:

estimating, during a settling time, a settled bioelectrical impedance value corresponding to a settled time after expiration of the settling time by,

measuring, via a bioelectrical impedance sensor electrically connected to electrodes, a measured bioelectrical impedance based on a value of a sensing voltage during a sensing time corresponding to a portion of the settling time shorter than an entirety of the settling time, the settling time being prior to the measured bioelectrical impedance reaching the settled bioelectrical impedance value at the settled time, and

compensating for the sensing time being shorter than the entirety of the settling time by digitally modeling the value of the measured bioelectrical impedance for the settling time in a fitting function based on changes in the sensing voltage to generate a modeled fitting function, and estimating the settled bioelectrical impedance value at the settled time based on the modeled fitting function; and

generating bio-data based on the estimated settled bioelectrical impedance value.

18. The operation method ofclaim 17, further comprising:

determining a contact error between the bioelectrical impedance sensor and a user by comparing the modeled fitting function with the value of the measured bioelectrical impedance.

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